Iterative feedback tuning—an overview

Abstract

Adaptive and iterative control algorithms based on explicit criterion minimization are briefly reviewed and an overview of one such algorithm, iterative feedback tuning (IFT) , is presented. The basic IFT algorithm is reviewed for both single-input/single-output and multi-input/multi-output systems. Subsequently the application to non-linear systems is discussed. Stability and robustness aspects are covered. A survey of existing extensions, applications and related methods is also provided. ; 16:373-395 H. HJALMARSSON Sensitivity modelsLater it was recognized that for linear time-invariant, processes, the sensitivity of any signal, sðtÞ say, in the system w.r.t. any scalar parameter r in the system, i.e. the partial derivative @sðtÞ=@r;

Performance optimization of piecewise affine variable-gain controllers for linear motion systems

“…Iterative feedback tuning concepts, see e.g. [27][28][29][30], can possibly be used in this context, although it should be investigated whether these concepts apply to the nonlinear piecewise affine variable-gain control feedback configuration as considered in this paper. In this section, the data-based approach has been applied successfully to the performance-based tuning of a piecewise affine variable gain controller for a wafer stage of an industrial wafer scanner.…”

Iterative feedback tuning of uncertain state space systems

“…An extensive overview of contributions and applications for this tuning method can be found in Gevers (2002) and Hjalmarsson (2002). The tuning method optimizes a set of control parameters, ρ, based on a performance cost function like Equation (7).…”

“…The main idea is to use closed loop data to determine an unbiased estimate of the cost function gradient with respect to the control parameters and use that estimate in a gradient based search algorithm. Iterative Feedback Tuning is designed to tune lower level controllers that are linear in the control parameters as, e.g., PID controllers (Hjalmarsson 2002, Gevers 2002). It has been tested in practice for PID control loops in Hjalmarsson et al (1998) and, more recently, for inventory control in Huusom et al (2007).…”

Data‐driven model reference control with asymptotically guaranteed stability

“…In recent years, several data-driven techniques have been proposed as an alternative to these model-based approaches [1,2,3,4]. In a data-driven approach, the aforementioned steps of 1 controller design are lumped together, resulting in a direct "data-to-controller" algorithm that uses a single optimization.…”

“…In Iterative Feedback Tuning (IFT) [1] and Iterative Correlation-based Tuning (ICbT) [3], a gradient approach is used to find a (local) optimum of the control objective. At each iteration, an experiment is used to evaluate the criterion or estimate the gradient, thus leading to an iterative scheme.…”